Implement real-time polyphonic pitch detection and feedback system for the melodic instrument player

Authors:
Geon-min Kim;Chang-hyun Kim;Soo-young Lee
Affiliations:
Department of Electrical Engineering, CNSL, Korea Advanced Institute of Science and Technology, Daejeon, Korea;Department of Bio and Brain Engineering, CNSL, Korea Advanced Institute of Science and Technology, Daejeon, Korea;Department of Electrical Engineering, CNSL, Korea Advanced Institute of Science and Technology, Daejeon, Korea
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
Year:
2012

Citing 2
Cited 0

A discriminative model for polyphonic piano transcription

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Abstract

This research proposes an automatic transcription-feedback system of music which help people to learn musical instruments by themselves. The focus of this research is piano. We develop real-time polyphonic pitch detectionfeedback system. For 'polyphonic pitch detection', we use inner product based similarity measure with discriminant note detection threshold and top down attention. Also, we develop two parallel processes on simulink and matlab separately for real-time system. On simulink workspace, real-time recording and signal flow management is implemented. This system takes 2mins. 12secs. for analyzing 1min. piece and have accuracy of pitch detection as 79.33% for test case (Chopin Nocturne Op.9 N.2).